« Matrice mal conditionnée » : différence entre les versions
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== Définition == | == Définition == | ||
In mathematics, a condition number is a number representative of the change of an output proportionate to a change in the input of a function. For example, if a small change in the input results in a small change in the output, the function produces a small condition number and is said to be well-conditioned. Alternatively, if a small change in the input results in a large change in the output, the function produces a large condition number and is defined as ill-conditioned. | |||
Imagine an example linear equation in which Ax = b. The condition number is, very generally, a representation of the rate at which the solution (x) changes with respect to changes in the value of (b). The condition number is a property of the matrix itself, not the algorithm. If the condition number of a matrix is too large, it is labeled as an ill-conditioned matrix. Condition numbers are representative of the accuracy of computing a matrix' inverse. For example, a well-conditioned matrix means its inverse can be computed with decent accuracy. Alternatively, an ill-conditioned matrix is not invertible and can have a condition number that is equal to infinity. | |||
== Français == | == Français == | ||
''' | '''matrice mal conditionnée''' | ||
== Anglais == | == Anglais == | ||
''' | '''ill-conditioned matrix''' | ||
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[https://deepai.org/machine-learning-glossary-and-terms/ill-conditioned-matrix Source : DeepAI.org ] | [https://deepai.org/machine-learning-glossary-and-terms/ill-conditioned-matrix Source : DeepAI.org ] | ||
[[Catégorie:DeepAI.org]] | [[Catégorie:DeepAI.org]] | ||
[[Catégorie:vocabulary]] | [[Catégorie:vocabulary]] |
Version du 17 septembre 2021 à 10:28
en construction
Définition
In mathematics, a condition number is a number representative of the change of an output proportionate to a change in the input of a function. For example, if a small change in the input results in a small change in the output, the function produces a small condition number and is said to be well-conditioned. Alternatively, if a small change in the input results in a large change in the output, the function produces a large condition number and is defined as ill-conditioned.
Imagine an example linear equation in which Ax = b. The condition number is, very generally, a representation of the rate at which the solution (x) changes with respect to changes in the value of (b). The condition number is a property of the matrix itself, not the algorithm. If the condition number of a matrix is too large, it is labeled as an ill-conditioned matrix. Condition numbers are representative of the accuracy of computing a matrix' inverse. For example, a well-conditioned matrix means its inverse can be computed with decent accuracy. Alternatively, an ill-conditioned matrix is not invertible and can have a condition number that is equal to infinity.
Français
matrice mal conditionnée
Anglais
ill-conditioned matrix
Contributeurs: Claire Gorjux, Jean Benoît Morel, wiki